Currently, e-commerce websites, whether business to business (B2B) or business to consumer (B2C), advertise their products in various ways. In particular, e-commerce websites commonly provide product recommendations that are tailored to a specific user/individual. These product recommendations may be based on, for example, a user's search history, browsing history, purchasing history, shipping history, geographic location, saved personal information, and other user information that may be collected by an organization. While these prior art systems and methods allow organizations to access superficial, or first-level demographic information about a user, they often do not provide in depth analysis into the user's interests, preferences, and personal beliefs.
In an attempt to overcome this problem, organizations have looked to a user's personal website, i.e., a social networking website, a professional profile, a personal blog, etc., for the purpose of gleaning additional information about the user. By its nature, a user's personal website may provide more complex and accurate personal information about the user because the personal website is user-created and edited. For example, an organization may use select keywords from a user's personal webpage in order to generate future product recommendations. But, even keywords taken from a personal webpage may be mistaken and/misinterpreted. In other words, the content of a personal webpage, standing alone, may not provide a full context for the keywords used in the personal webpage. Furthermore, because known searching capabilities are sometimes insufficient for finding relevant information within a user's personal website, existing product recommendation systems still often fail to provide recommendations that consider in-depth, fully accurate information about a user's interests and preferences even when information in a user's personal website is considered.